Platform Engineering Manager – AI-Driven, Scalable Systems

United States Digital Space LLC

Greater London

On-site

GBP 100,000 - 140,000

Full time

14 days+

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Job summary

JPMorgan Chase is hiring an Engineering Manager (Platform) to lead a high-performing squad within the Accelerator Business Platform Team in the UK. You will bridge technical strategy and business goals, nurture talent, and drive a culture of diversity, equity, inclusion, and respect.

You will guide growth, health, and delivery of the engineering team ensuring scalable products aligned with the company mission.

Qualifications

Experience leading technologists to manage and solve complex technical challenges.
Proven people-management or team-lead experience.
Strong background in software engineering, including system design, cloud native systems, and Kubernetes.
Experience managing production systems, including on-call rotations, incident response, and reliability engineering.
Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including governance/ways of working and measuring outcomes.

Responsibilities

Provide direction, coaching for a team of software engineers, fostering an inclusive, high-performance culture.
Oversee end-to-end delivery of platform initiatives, translating requirements into technical roadmaps and ensuring operational stability.
Drive engineering standards and best practices, promoting high-quality code, robust release processes, and scalable infrastructure.
Partner with senior leadership to set the long-term technical vision for the platform, aligning with business outcomes and regulatory requirements.
Champion a 'you-build-it-you-run-it' culture, overseeing incident response and identifying opportunities to automate remediation.
Ensure successful collaboration across teams and stakeholders, driving consensus on architectural and delivery trade-offs.
Identify and mitigate issues to execute a book of work, contributing to communities of practice and adoption of leading-edge technologies.
Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes; establishes measurable expectations and ensures secure handling of inputs/outputs.